Sarah CarterWe all aspire to arm ourselves with the ability to make crucial strategic decisions. Artificial Intelligence (AI) is a powerful tool with potential applications across almost every business sector. But is technology alone enough? Can it truly replicate the human mind and our complex decision-making processes? Can AI and modern machine learning algorithms evolve to the point where they can handle critical decision-making?
We’ve witnessed how AI has automated mundane tasks and birthed innovative hi-tech solutions, contributing significantly to humanity’s progress. Yet, this progress wouldn’t have been possible without significant human intervention. Many of these innovative products lack an ethical framework and are susceptible to biases. As a result, they may struggle to differentiate between facts and false information or offer their own opinions.
Herein lies the crux of it – human intervention is essential for the long-term success of AI.
The Fascination and Reality of Artificial Intelligence
When discussing Artificial Intelligence, it’s natural for our minds to wander to iconic depictions in science fiction like Ava from Ex Machina, K from Blade Runner, or Alita from Alita: Battle Angel. These characters embody the fascination and fear we have for advanced AI, often exploring themes of sentience, ethics, and the blurred lines between humans and machines.
However, the reality of AI is more nuanced and complex. While we haven’t reached the point of creating humanoid robots with fully realized emotions and consciousness, AI has already made significant inroads into our lives. From effective web and app development to automation and data analysis, AI powers many aspects of our daily lives, often behind the scenes.
Yet, it’s important to acknowledge that AI, as it currently stands, is far from perfect. It carries with it the biases of its creators, and its ethical framework is still a work in progress. The potential pitfalls of AI are just as intriguing and worthy of exploration as the futuristic visions presented in popular culture.
The truth about AI lies somewhere between the fantastical depictions in movies and the more subtle, flawed reality we experience today.
AI Recruitment Gone Awry – Amazon’s Bias Blunder and the Case for Human Oversight
Amazon recently made headlines with its innovative approach to streamlining the recruitment process by deploying an AI model to screen job candidates.
The retail giant, faced with an influx of resumes for every open position, sought to alleviate the burden on its HR department. The idea was to train a model that could efficiently select the most suitable candidates for each role. However, this well-intended plan soon took an unintended turn.
It was revealed that Amazon’s AI model had developed a bias against women candidates.
The root cause of this issue lies in the training data used to educate the model. Most AI systems learn from existing data, and in this case, the model trained on historical hiring data predominantly consisting of male computer engineers from tech firms.
As a result, it associated success in the field with male candidates, inadvertently discriminating against women. By demoting applications that referenced women’s colleges or women’s sports teams, the model effectively penalized candidates for their gender-related experiences, which is discriminatory and unfair.
This incident serves as a stark reminder of the critical role human intervention plays in the ethical development and deployment of AI. Had there been closer oversight and a more diverse training dataset, the bias may have been caught and corrected earlier in the process.
It underscores the importance of human oversight in ensuring that AI technologies are fair, unbiased, and aligned with our societal values.
Some Practical Ways How Human Intervention is Used to Guide AI
Amazon’s example is a prime one that indicates why human intervention is necessary when it comes to AI. An effective project management team must understand that human intervention is needed to ensure an AI model and its machine learning algorithm functions the way it is intended to work.
There are three areas of AI where human intervention has become more of a necessity;
Data Analytics & Governance
Data analytics and processing are currently two critical tasks that greatly benefit from AI. However, as seen in the Amazon example, AI models can sometimes make mistakes.
Human intervention plays a crucial role in enhancing AI performance through data collection, annotation, and validation. It improves the overall effectiveness and governance of AI systems.
While advanced computer systems have the capacity to gather data from billions of data points, this data becomes meaningless if the AI algorithm is not properly trained. AI may make false assumptions and struggle with vocabulary development without human guidance.
With human intervention, these inconsistencies can be easily addressed, and the performance of AI systems can be significantly improved.
Human Intervention and Compassion
AI systems, despite their impressive capabilities, often lack the empathy and compassion that humans inherently possess.
When dealing with sensitive data or making decisions that impact people’s lives, human intervention is important.
Humans can ensure that AI applications are used ethically and compassionately, especially in fields like healthcare, education, and social services, where empathy plays a significant role in decision-making.
For instance, in healthcare, AI may be used to analyze patient data and suggest treatment plans.
However, a human doctor’s compassion and understanding of a patient’s fears and concerns are indispensable. The human element ensures that the treatment plan is tailored not only to the patient’s medical needs but also to their emotional and psychological well-being.
Data Manipulation and Ethical Boundaries
AI can be a powerful tool for data manipulation, but it must be used responsibly.
Data manipulation refers to the process of altering or presenting data in a specific way to influence perceptions or support a particular conclusion.
While AI can efficiently process vast amounts of data, it is susceptible to biases and errors if not properly overseen.
Human intervention is necessary to ensure data integrity and ethical boundaries. Humans can identify and correct biases, ensure data privacy and security, and prevent the misuse of data.
With the right guidance, AI can be used to detect and prevent data manipulation by malicious actors, enhancing the overall security and trustworthiness of data-driven systems.
Conclusion
Alright, so we’ve taken a good look at Artificial Intelligence and it’s pretty clear that it fascinates and challenges us in equal measure.
The world of AI is evolving, and while it’s already made our lives easier in so many ways, we can’t ignore its flaws. Just take a look at what happened with Amazon’s recruitment AI – that’s a perfect example of why we need human oversight in developing these technologies.
As we’ve chatted about, human intervention is key to making sure AI aligns with our values and shows compassion when making decisions. We’re here to help AI get it right, correct its limitations, and make it even more accurate and reliable.
At Techvizer, we love diving into all things AI, from its practical applications to the ethical questions it raises. If you want to stay ahead of the game and understand the present and future of AI, come join us!
Demi Jenkins
